code: def get_output_feature_tensor(
      output_dict: Dict[str, torch.Tensor],
      feature_name: str,
      tensor_name: str,
  ) -> torch.Tensor:
      """Returns a tensor related for the given feature_name and tensor_name."""
      concat_name = get_feature_concat_name(feature_name, tensor_name)
      if concat_name not in output_dict:
          raise ValueError(
              f"Could not find {tensor_name} for {feature_name} in the output_dict with keys: {output_dict.keys()}"
          )
      return output_dict[
          get_feature_concat_name(feature_name, tensor_name)
      ]
  
file_path: ludwig/ludwig/utils/output_feature_utils.py
imports: from typing import Dict, List
  import numpy
  import torch
  from ludwig.utils.torch_utils import sequence_length_3D, sequence_mask
label_desc: Use image node_id 5 for calling a global function with example usage: get_output_feature_tensor(output_dict, feature_name, tensor_name) and returns: output_dict